The rise of prediction markets reshapes strategies in the betting sector
Prediction markets (platforms that allow users to trade on the probabilities of future events) are gaining increasing prominence in the digital landscape and attracting the interest of companies that operate at the intersection of content, betting and technology. In the United States, this model has been growing rapidly and is beginning to influence the strategies of global media groups specialising in sports betting. As interest in the sector expands, many users are also searching for explanations about how prediction markets work, how to trade sports prediction markets and how prediction markets differ from sports betting.
Among the companies that have started to explore this segment is Better Collective, which is seeking to expand into products based on data and user behaviour. The strong demand for content related to probabilities, trends and event analysis has signalled a change in the profile of the audience engaging in online entertainment.
What prediction markets are and why they are growing
Unlike traditional betting, prediction markets operate in a way similar to financial exchanges. Users buy and sell contracts whose value varies according to the perceived probability of a certain event happening, whether it is a sporting result, an election, an awards ceremony or even an economic indicator.
This format has attracted many participants interested not only in entertainment but also in data analysis and crowd behaviour. In theory, the greater the number of participants trading contracts, the more efficient probability projections tend to be. For many users, understanding prediction market odds and implied probability is one of the main attractions, as prices fluctuate dynamically according to market sentiment and collective expectations.
In the United States, interest in the topic increased mainly after the latest elections, when some prediction markets demonstrated an ability to anticipate trends that did not always appear clearly in traditional polls. At the same time, improvements in platform experience, such as more intuitive interfaces and greater liquidity, contributed to making this type of product more accessible. The growing accessibility has also encouraged new audiences to learn how to trade sports prediction markets, particularly among users already familiar with fantasy sports and financial trading apps.
Data help explain the growing interest
The latest industry reports indicate that the trading volume in this type of market has grown significantly over the past two years. The continued expansion of digitalisation, the popularisation of online communities focused on probability analysis, and the increase in real-time content consumption have helped create a favourable environment for expansion.
In addition, younger audiences have shown greater familiarity with digital models built around data, rankings and projections. This behaviour brings prediction markets closer to other already established digital formats, such as fantasy sports, social trading and simplified investment platforms. The context explains why media companies specialised in betting have begun to see the segment as a new avenue for growth.
In Better Collective‘s case, the strategy is primarily linked to the development of editorial hubs and educational content about how these markets work. The logic follows a model already used in the sports betting sector: attracting qualified audiences through analysis, information and tools that support decision-making. This educational approach also reflects rising search demand for topics related to how prediction markets work and the mechanics behind market-based forecasting platforms.
This type of strategy aims to increase organic traffic, strengthen search engine positioning and create new monetisation opportunities. At the same time, the integration between content and trading platforms tends to reduce the distance between information consumption and active user participation.
Between entertainment and speculation
Despite the enthusiasm surrounding the growth of prediction markets, the model also raises questions. Regulators and specialists discuss to what extent these products should be treated as betting, investments or a new hybrid category. An example is the recent ban on Polymarket in Argentina, after the platform had already been restricted in several other countries.
There are concerns related to consumer protection, platform transparency and possible behavioural impacts, especially in environments with little regulation. The risk that users may confuse probabilistic analysis with a guarantee of financial gains is one of the most frequently cited points.
On the other hand, supporters of the model argue that these markets can help improve the quality of collective forecasts and broaden access to data interpretation tools. They also see them as another form of entertainment, both for users already engaged with betting markets and for those unfamiliar with prediction markets.
This article was first published in Portuguese on 20 March 2026.
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